Add files using upload-large-folder tool

parrot/lib/python3.10/site-packages/huggingface_hub/commands/_cli_utils.py

@@ -0,0 +1,69 @@
+# Copyright 2022 The HuggingFace Team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains a utility for good-looking prints."""
+
+import os
+from typing import List, Union
+
+
+class ANSI:
+    """
+    Helper for en.wikipedia.org/wiki/ANSI_escape_code
+    """
+
+    _bold = "\u001b[1m"
+    _gray = "\u001b[90m"
+    _red = "\u001b[31m"
+    _reset = "\u001b[0m"
+    _yellow = "\u001b[33m"
+
+    @classmethod
+    def bold(cls, s: str) -> str:
+        return cls._format(s, cls._bold)
+
+    @classmethod
+    def gray(cls, s: str) -> str:
+        return cls._format(s, cls._gray)
+
+    @classmethod
+    def red(cls, s: str) -> str:
+        return cls._format(s, cls._bold + cls._red)
+
+    @classmethod
+    def yellow(cls, s: str) -> str:
+        return cls._format(s, cls._yellow)
+
+    @classmethod
+    def _format(cls, s: str, code: str) -> str:
+        if os.environ.get("NO_COLOR"):
+            # See https://no-color.org/
+            return s
+        return f"{code}{s}{cls._reset}"
+
+
+def tabulate(rows: List[List[Union[str, int]]], headers: List[str]) -> str:
+    """
+    Inspired by:
+
+    - stackoverflow.com/a/8356620/593036
+    - stackoverflow.com/questions/9535954/printing-lists-as-tabular-data
+    """
+    col_widths = [max(len(str(x)) for x in col) for col in zip(*rows, headers)]
+    row_format = ("{{:{}}} " * len(headers)).format(*col_widths)
+    lines = []
+    lines.append(row_format.format(*headers))
+    lines.append(row_format.format(*["-" * w for w in col_widths]))
+    for row in rows:
+        lines.append(row_format.format(*row))
+    return "\n".join(lines)

parrot/lib/python3.10/site-packages/huggingface_hub/commands/delete_cache.py

@@ -0,0 +1,428 @@
+# coding=utf-8
+# Copyright 2022-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains command to delete some revisions from the HF cache directory.
+
+Usage:
+    huggingface-cli delete-cache
+    huggingface-cli delete-cache --disable-tui
+    huggingface-cli delete-cache --dir ~/.cache/huggingface/hub
+
+NOTE:
+    This command is based on `InquirerPy` to build the multiselect menu in the terminal.
+    This dependency has to be installed with `pip install huggingface_hub[cli]`. Since
+    we want to avoid as much as possible cross-platform issues, I chose a library that
+    is built on top of `python-prompt-toolkit` which seems to be a reference in terminal
+    GUI (actively maintained on both Unix and Windows, 7.9k stars).
+
+    For the moment, the TUI feature is in beta.
+
+    See:
+    - https://github.com/kazhala/InquirerPy
+    - https://inquirerpy.readthedocs.io/en/latest/
+    - https://github.com/prompt-toolkit/python-prompt-toolkit
+
+    Other solutions could have been:
+    - `simple_term_menu`: would be good as well for our use case but some issues suggest
+      that Windows is less supported.
+      See: https://github.com/IngoMeyer441/simple-term-menu
+    - `PyInquirer`: very similar to `InquirerPy` but older and not maintained anymore.
+      In particular, no support of Python3.10.
+      See: https://github.com/CITGuru/PyInquirer
+    - `pick` (or `pickpack`): easy to use and flexible but built on top of Python's
+      standard library `curses` that is specific to Unix (not implemented on Windows).
+      See https://github.com/wong2/pick and https://github.com/anafvana/pickpack.
+    - `inquirer`: lot of traction (700 stars) but explicitly states "experimental
+      support of Windows". Not built on top of `python-prompt-toolkit`.
+      See https://github.com/magmax/python-inquirer
+
+TODO: add support for `huggingface-cli delete-cache aaaaaa bbbbbb cccccc (...)` ?
+TODO: add "--keep-last" arg to delete revisions that are not on `main` ref
+TODO: add "--filter" arg to filter repositories by name ?
+TODO: add "--sort" arg to sort by size ?
+TODO: add "--limit" arg to limit to X repos ?
+TODO: add "-y" arg for immediate deletion ?
+See discussions in https://github.com/huggingface/huggingface_hub/issues/1025.
+"""
+
+import os
+from argparse import Namespace, _SubParsersAction
+from functools import wraps
+from tempfile import mkstemp
+from typing import Any, Callable, Iterable, List, Optional, Union
+
+from ..utils import CachedRepoInfo, CachedRevisionInfo, HFCacheInfo, scan_cache_dir
+from . import BaseHuggingfaceCLICommand
+from ._cli_utils import ANSI
+
+
+try:
+    from InquirerPy import inquirer
+    from InquirerPy.base.control import Choice
+    from InquirerPy.separator import Separator
+
+    _inquirer_py_available = True
+except ImportError:
+    _inquirer_py_available = False
+
+
+def require_inquirer_py(fn: Callable) -> Callable:
+    """Decorator to flag methods that require `InquirerPy`."""
+
+    # TODO: refactor this + imports in a unified pattern across codebase
+    @wraps(fn)
+    def _inner(*args, **kwargs):
+        if not _inquirer_py_available:
+            raise ImportError(
+                "The `delete-cache` command requires extra dependencies to work with"
+                " the TUI.\nPlease run `pip install huggingface_hub[cli]` to install"
+                " them.\nOtherwise, disable TUI using the `--disable-tui` flag."
+            )
+
+        return fn(*args, **kwargs)
+
+    return _inner
+
+
+# Possibility for the user to cancel deletion
+_CANCEL_DELETION_STR = "CANCEL_DELETION"
+
+
+class DeleteCacheCommand(BaseHuggingfaceCLICommand):
+    @staticmethod
+    def register_subcommand(parser: _SubParsersAction):
+        delete_cache_parser = parser.add_parser("delete-cache", help="Delete revisions from the cache directory.")
+
+        delete_cache_parser.add_argument(
+            "--dir",
+            type=str,
+            default=None,
+            help="cache directory (optional). Default to the default HuggingFace cache.",
+        )
+
+        delete_cache_parser.add_argument(
+            "--disable-tui",
+            action="store_true",
+            help=(
+                "Disable Terminal User Interface (TUI) mode. Useful if your"
+                " platform/terminal doesn't support the multiselect menu."
+            ),
+        )
+
+        delete_cache_parser.set_defaults(func=DeleteCacheCommand)
+
+    def __init__(self, args: Namespace) -> None:
+        self.cache_dir: Optional[str] = args.dir
+        self.disable_tui: bool = args.disable_tui
+
+    def run(self):
+        """Run `delete-cache` command with or without TUI."""
+        # Scan cache directory
+        hf_cache_info = scan_cache_dir(self.cache_dir)
+
+        # Manual review from the user
+        if self.disable_tui:
+            selected_hashes = _manual_review_no_tui(hf_cache_info, preselected=[])
+        else:
+            selected_hashes = _manual_review_tui(hf_cache_info, preselected=[])
+
+        # If deletion is not cancelled
+        if len(selected_hashes) > 0 and _CANCEL_DELETION_STR not in selected_hashes:
+            confirm_message = _get_expectations_str(hf_cache_info, selected_hashes) + " Confirm deletion ?"
+
+            # Confirm deletion
+            if self.disable_tui:
+                confirmed = _ask_for_confirmation_no_tui(confirm_message)
+            else:
+                confirmed = _ask_for_confirmation_tui(confirm_message)
+
+            # Deletion is confirmed
+            if confirmed:
+                strategy = hf_cache_info.delete_revisions(*selected_hashes)
+                print("Start deletion.")
+                strategy.execute()
+                print(
+                    f"Done. Deleted {len(strategy.repos)} repo(s) and"
+                    f" {len(strategy.snapshots)} revision(s) for a total of"
+                    f" {strategy.expected_freed_size_str}."
+                )
+                return
+
+        # Deletion is cancelled
+        print("Deletion is cancelled. Do nothing.")
+
+
+@require_inquirer_py
+def _manual_review_tui(hf_cache_info: HFCacheInfo, preselected: List[str]) -> List[str]:
+    """Ask the user for a manual review of the revisions to delete.
+
+    Displays a multi-select menu in the terminal (TUI).
+    """
+    # Define multiselect list
+    choices = _get_tui_choices_from_scan(repos=hf_cache_info.repos, preselected=preselected)
+    checkbox = inquirer.checkbox(
+        message="Select revisions to delete:",
+        choices=choices,  # List of revisions with some pre-selection
+        cycle=False,  # No loop between top and bottom
+        height=100,  # Large list if possible
+        # We use the instruction to display to the user the expected effect of the
+        # deletion.
+        instruction=_get_expectations_str(
+            hf_cache_info,
+            selected_hashes=[c.value for c in choices if isinstance(c, Choice) and c.enabled],
+        ),
+        # We use the long instruction to should keybindings instructions to the user
+        long_instruction="Press <space> to select, <enter> to validate and <ctrl+c> to quit without modification.",
+        # Message that is displayed once the user validates its selection.
+        transformer=lambda result: f"{len(result)} revision(s) selected.",
+    )
+
+    # Add a callback to update the information line when a revision is
+    # selected/unselected
+    def _update_expectations(_) -> None:
+        # Hacky way to dynamically set an instruction message to the checkbox when
+        # a revision hash is selected/unselected.
+        checkbox._instruction = _get_expectations_str(
+            hf_cache_info,
+            selected_hashes=[choice["value"] for choice in checkbox.content_control.choices if choice["enabled"]],
+        )
+
+    checkbox.kb_func_lookup["toggle"].append({"func": _update_expectations})
+
+    # Finally display the form to the user.
+    try:
+        return checkbox.execute()
+    except KeyboardInterrupt:
+        return []  # Quit without deletion
+
+
+@require_inquirer_py
+def _ask_for_confirmation_tui(message: str, default: bool = True) -> bool:
+    """Ask for confirmation using Inquirer."""
+    return inquirer.confirm(message, default=default).execute()
+
+
+def _get_tui_choices_from_scan(repos: Iterable[CachedRepoInfo], preselected: List[str]) -> List:
+    """Build a list of choices from the scanned repos.
+
+    Args:
+        repos (*Iterable[`CachedRepoInfo`]*):
+            List of scanned repos on which we want to delete revisions.
+        preselected (*List[`str`]*):
+            List of revision hashes that will be preselected.
+
+    Return:
+        The list of choices to pass to `inquirer.checkbox`.
+    """
+    choices: List[Union[Choice, Separator]] = []
+
+    # First choice is to cancel the deletion. If selected, nothing will be deleted,
+    # no matter the other selected items.
+    choices.append(
+        Choice(
+            _CANCEL_DELETION_STR,
+            name="None of the following (if selected, nothing will be deleted).",
+            enabled=False,
+        )
+    )
+
+    # Display a separator per repo and a Choice for each revisions of the repo
+    for repo in sorted(repos, key=_repo_sorting_order):
+        # Repo as separator
+        choices.append(
+            Separator(
+                f"\n{repo.repo_type.capitalize()} {repo.repo_id} ({repo.size_on_disk_str},"
+                f" used {repo.last_accessed_str})"
+            )
+        )
+        for revision in sorted(repo.revisions, key=_revision_sorting_order):
+            # Revision as choice
+            choices.append(
+                Choice(
+                    revision.commit_hash,
+                    name=(
+                        f"{revision.commit_hash[:8]}:"
+                        f" {', '.join(sorted(revision.refs)) or '(detached)'} #"
+                        f" modified {revision.last_modified_str}"
+                    ),
+                    enabled=revision.commit_hash in preselected,
+                )
+            )
+
+    # Return choices
+    return choices
+
+
+def _manual_review_no_tui(hf_cache_info: HFCacheInfo, preselected: List[str]) -> List[str]:
+    """Ask the user for a manual review of the revisions to delete.
+
+    Used when TUI is disabled. Manual review happens in a separate tmp file that the
+    user can manually edit.
+    """
+    # 1. Generate temporary file with delete commands.
+    fd, tmp_path = mkstemp(suffix=".txt")  # suffix to make it easier to find by editors
+    os.close(fd)
+
+    lines = []
+    for repo in sorted(hf_cache_info.repos, key=_repo_sorting_order):
+        lines.append(
+            f"\n# {repo.repo_type.capitalize()} {repo.repo_id} ({repo.size_on_disk_str},"
+            f" used {repo.last_accessed_str})"
+        )
+        for revision in sorted(repo.revisions, key=_revision_sorting_order):
+            lines.append(
+                # Deselect by prepending a '#'
+                f"{'' if revision.commit_hash in preselected else '#'}   "
+                f" {revision.commit_hash} # Refs:"
+                # Print `refs` as comment on same line
+                f" {', '.join(sorted(revision.refs)) or '(detached)'} # modified"
+                # Print `last_modified` as comment on same line
+                f" {revision.last_modified_str}"
+            )
+
+    with open(tmp_path, "w") as f:
+        f.write(_MANUAL_REVIEW_NO_TUI_INSTRUCTIONS)
+        f.write("\n".join(lines))
+
+    # 2. Prompt instructions to user.
+    instructions = f"""
+    TUI is disabled. In order to select which revisions you want to delete, please edit
+    the following file using the text editor of your choice. Instructions for manual
+    editing are located at the beginning of the file. Edit the file, save it and confirm
+    to continue.
+    File to edit: {ANSI.bold(tmp_path)}
+    """
+    print("\n".join(line.strip() for line in instructions.strip().split("\n")))
+
+    # 3. Wait for user confirmation.
+    while True:
+        selected_hashes = _read_manual_review_tmp_file(tmp_path)
+        if _ask_for_confirmation_no_tui(
+            _get_expectations_str(hf_cache_info, selected_hashes) + " Continue ?",
+            default=False,
+        ):
+            break
+
+    # 4. Return selected_hashes
+    os.remove(tmp_path)
+    return selected_hashes
+
+
+def _ask_for_confirmation_no_tui(message: str, default: bool = True) -> bool:
+    """Ask for confirmation using pure-python."""
+    YES = ("y", "yes", "1")
+    NO = ("n", "no", "0")
+    DEFAULT = ""
+    ALL = YES + NO + (DEFAULT,)
+    full_message = message + (" (Y/n) " if default else " (y/N) ")
+    while True:
+        answer = input(full_message).lower()
+        if answer == DEFAULT:
+            return default
+        if answer in YES:
+            return True
+        if answer in NO:
+            return False
+        print(f"Invalid input. Must be one of {ALL}")
+
+
+def _get_expectations_str(hf_cache_info: HFCacheInfo, selected_hashes: List[str]) -> str:
+    """Format a string to display to the user how much space would be saved.
+
+    Example:
+    ```
+    >>> _get_expectations_str(hf_cache_info, selected_hashes)
+    '7 revisions selected counting for 4.3G.'
+    ```
+    """
+    if _CANCEL_DELETION_STR in selected_hashes:
+        return "Nothing will be deleted."
+    strategy = hf_cache_info.delete_revisions(*selected_hashes)
+    return f"{len(selected_hashes)} revisions selected counting for {strategy.expected_freed_size_str}."
+
+
+def _read_manual_review_tmp_file(tmp_path: str) -> List[str]:
+    """Read the manually reviewed instruction file and return a list of revision hash.
+
+    Example:
+        ```txt
+        # This is the tmp file content
+        ###
+
+        # Commented out line
+        123456789 # revision hash
+
+        # Something else
+        #      a_newer_hash # 2 days ago
+            an_older_hash # 3 days ago
+        ```
+
+        ```py
+        >>> _read_manual_review_tmp_file(tmp_path)
+        ['123456789', 'an_older_hash']
+        ```
+    """
+    with open(tmp_path) as f:
+        content = f.read()
+
+    # Split lines
+    lines = [line.strip() for line in content.split("\n")]
+
+    # Filter commented lines
+    selected_lines = [line for line in lines if not line.startswith("#")]
+
+    # Select only before comment
+    selected_hashes = [line.split("#")[0].strip() for line in selected_lines]
+
+    # Return revision hashes
+    return [hash for hash in selected_hashes if len(hash) > 0]
+
+
+_MANUAL_REVIEW_NO_TUI_INSTRUCTIONS = f"""
+# INSTRUCTIONS
+# ------------
+# This is a temporary file created by running `huggingface-cli delete-cache` with the
+# `--disable-tui` option. It contains a set of revisions that can be deleted from your
+# local cache directory.
+#
+# Please manually review the revisions you want to delete:
+#   - Revision hashes can be commented out with '#'.
+#   - Only non-commented revisions in this file will be deleted.
+#   - Revision hashes that are removed from this file are ignored as well.
+#   - If `{_CANCEL_DELETION_STR}` line is uncommented, the all cache deletion is cancelled and
+#     no changes will be applied.
+#
+# Once you've manually reviewed this file, please confirm deletion in the terminal. This
+# file will be automatically removed once done.
+# ------------
+
+# KILL SWITCH
+# ------------
+# Un-comment following line to completely cancel the deletion process
+# {_CANCEL_DELETION_STR}
+# ------------
+
+# REVISIONS
+# ------------
+""".strip()
+
+
+def _repo_sorting_order(repo: CachedRepoInfo) -> Any:
+    # First split by Dataset/Model, then sort by last accessed (oldest first)
+    return (repo.repo_type, repo.last_accessed)
+
+
+def _revision_sorting_order(revision: CachedRevisionInfo) -> Any:
+    # Sort by last modified (oldest first)
+    return revision.last_modified

parrot/lib/python3.10/site-packages/huggingface_hub/commands/lfs.py

@@ -0,0 +1,200 @@
+"""
+Implementation of a custom transfer agent for the transfer type "multipart" for
+git-lfs.
+
+Inspired by:
+github.com/cbartz/git-lfs-swift-transfer-agent/blob/master/git_lfs_swift_transfer.py
+
+Spec is: github.com/git-lfs/git-lfs/blob/master/docs/custom-transfers.md
+
+
+To launch debugger while developing:
+
+``` [lfs "customtransfer.multipart"]
+path = /path/to/huggingface_hub/.env/bin/python args = -m debugpy --listen 5678
+--wait-for-client
+/path/to/huggingface_hub/src/huggingface_hub/commands/huggingface_cli.py
+lfs-multipart-upload ```"""
+
+import json
+import os
+import subprocess
+import sys
+from argparse import _SubParsersAction
+from typing import Dict, List, Optional
+
+from huggingface_hub.commands import BaseHuggingfaceCLICommand
+from huggingface_hub.lfs import LFS_MULTIPART_UPLOAD_COMMAND
+
+from ..utils import get_session, hf_raise_for_status, logging
+from ..utils._lfs import SliceFileObj
+
+
+logger = logging.get_logger(__name__)
+
+
+class LfsCommands(BaseHuggingfaceCLICommand):
+    """
+    Implementation of a custom transfer agent for the transfer type "multipart"
+    for git-lfs. This lets users upload large files >5GB 🔥. Spec for LFS custom
+    transfer agent is:
+    https://github.com/git-lfs/git-lfs/blob/master/docs/custom-transfers.md
+
+    This introduces two commands to the CLI:
+
+    1. $ huggingface-cli lfs-enable-largefiles
+
+    This should be executed once for each model repo that contains a model file
+    >5GB. It's documented in the error message you get if you just try to git
+    push a 5GB file without having enabled it before.
+
+    2. $ huggingface-cli lfs-multipart-upload
+
+    This command is called by lfs directly and is not meant to be called by the
+    user.
+    """
+
+    @staticmethod
+    def register_subcommand(parser: _SubParsersAction):
+        enable_parser = parser.add_parser(
+            "lfs-enable-largefiles", help="Configure your repository to enable upload of files > 5GB."
+        )
+        enable_parser.add_argument("path", type=str, help="Local path to repository you want to configure.")
+        enable_parser.set_defaults(func=lambda args: LfsEnableCommand(args))
+
+        # Command will get called by git-lfs, do not call it directly.
+        upload_parser = parser.add_parser(LFS_MULTIPART_UPLOAD_COMMAND, add_help=False)
+        upload_parser.set_defaults(func=lambda args: LfsUploadCommand(args))
+
+
+class LfsEnableCommand:
+    def __init__(self, args):
+        self.args = args
+
+    def run(self):
+        local_path = os.path.abspath(self.args.path)
+        if not os.path.isdir(local_path):
+            print("This does not look like a valid git repo.")
+            exit(1)
+        subprocess.run(
+            "git config lfs.customtransfer.multipart.path huggingface-cli".split(),
+            check=True,
+            cwd=local_path,
+        )
+        subprocess.run(
+            f"git config lfs.customtransfer.multipart.args {LFS_MULTIPART_UPLOAD_COMMAND}".split(),
+            check=True,
+            cwd=local_path,
+        )
+        print("Local repo set up for largefiles")
+
+
+def write_msg(msg: Dict):
+    """Write out the message in Line delimited JSON."""
+    msg_str = json.dumps(msg) + "\n"
+    sys.stdout.write(msg_str)
+    sys.stdout.flush()
+
+
+def read_msg() -> Optional[Dict]:
+    """Read Line delimited JSON from stdin."""
+    msg = json.loads(sys.stdin.readline().strip())
+
+    if "terminate" in (msg.get("type"), msg.get("event")):
+        # terminate message received
+        return None
+
+    if msg.get("event") not in ("download", "upload"):
+        logger.critical("Received unexpected message")
+        sys.exit(1)
+
+    return msg
+
+
+class LfsUploadCommand:
+    def __init__(self, args) -> None:
+        self.args = args
+
+    def run(self) -> None:
+        # Immediately after invoking a custom transfer process, git-lfs
+        # sends initiation data to the process over stdin.
+        # This tells the process useful information about the configuration.
+        init_msg = json.loads(sys.stdin.readline().strip())
+        if not (init_msg.get("event") == "init" and init_msg.get("operation") == "upload"):
+            write_msg({"error": {"code": 32, "message": "Wrong lfs init operation"}})
+            sys.exit(1)
+
+        # The transfer process should use the information it needs from the
+        # initiation structure, and also perform any one-off setup tasks it
+        # needs to do. It should then respond on stdout with a simple empty
+        # confirmation structure, as follows:
+        write_msg({})
+
+        # After the initiation exchange, git-lfs will send any number of
+        # transfer requests to the stdin of the transfer process, in a serial sequence.
+        while True:
+            msg = read_msg()
+            if msg is None:
+                # When all transfers have been processed, git-lfs will send
+                # a terminate event to the stdin of the transfer process.
+                # On receiving this message the transfer process should
+                # clean up and terminate. No response is expected.
+                sys.exit(0)
+
+            oid = msg["oid"]
+            filepath = msg["path"]
+            completion_url = msg["action"]["href"]
+            header = msg["action"]["header"]
+            chunk_size = int(header.pop("chunk_size"))
+            presigned_urls: List[str] = list(header.values())
+
+            # Send a "started" progress event to allow other workers to start.
+            # Otherwise they're delayed until first "progress" event is reported,
+            # i.e. after the first 5GB by default (!)
+            write_msg(
+                {
+                    "event": "progress",
+                    "oid": oid,
+                    "bytesSoFar": 1,
+                    "bytesSinceLast": 0,
+                }
+            )
+
+            parts = []
+            with open(filepath, "rb") as file:
+                for i, presigned_url in enumerate(presigned_urls):
+                    with SliceFileObj(
+                        file,
+                        seek_from=i * chunk_size,
+                        read_limit=chunk_size,
+                    ) as data:
+                        r = get_session().put(presigned_url, data=data)
+                        hf_raise_for_status(r)
+                        parts.append(
+                            {
+                                "etag": r.headers.get("etag"),
+                                "partNumber": i + 1,
+                            }
+                        )
+                        # In order to support progress reporting while data is uploading / downloading,
+                        # the transfer process should post messages to stdout
+                        write_msg(
+                            {
+                                "event": "progress",
+                                "oid": oid,
+                                "bytesSoFar": (i + 1) * chunk_size,
+                                "bytesSinceLast": chunk_size,
+                            }
+                        )
+                        # Not precise but that's ok.
+
+            r = get_session().post(
+                completion_url,
+                json={
+                    "oid": oid,
+                    "parts": parts,
+                },
+            )
+            hf_raise_for_status(r)
+
+            write_msg({"event": "complete", "oid": oid})

parrot/lib/python3.10/site-packages/huggingface_hub/commands/repo_files.py

@@ -0,0 +1,128 @@
+# coding=utf-8
+# Copyright 2023-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""Contains command to update or delete files in a repository using the CLI.
+
+Usage:
+    # delete all
+    huggingface-cli repo-files <repo_id> delete "*"
+
+    # delete single file
+    huggingface-cli repo-files <repo_id> delete file.txt
+
+    # delete single folder
+    huggingface-cli repo-files <repo_id> delete folder/
+
+    # delete multiple
+    huggingface-cli repo-files <repo_id> delete file.txt folder/ file2.txt
+
+    # delete multiple patterns
+    huggingface-cli repo-files <repo_id> delete file.txt "*.json" "folder/*.parquet"
+
+    # delete from different revision / repo-type
+    huggingface-cli repo-files <repo_id> delete file.txt --revision=refs/pr/1 --repo-type=dataset
+"""
+
+from argparse import _SubParsersAction
+from typing import List, Optional
+
+from huggingface_hub import logging
+from huggingface_hub.commands import BaseHuggingfaceCLICommand
+from huggingface_hub.hf_api import HfApi
+
+
+logger = logging.get_logger(__name__)
+
+
+class DeleteFilesSubCommand:
+    def __init__(self, args) -> None:
+        self.args = args
+        self.repo_id: str = args.repo_id
+        self.repo_type: Optional[str] = args.repo_type
+        self.revision: Optional[str] = args.revision
+        self.api: HfApi = HfApi(token=args.token, library_name="huggingface-cli")
+        self.patterns: List[str] = args.patterns
+        self.commit_message: Optional[str] = args.commit_message
+        self.commit_description: Optional[str] = args.commit_description
+        self.create_pr: bool = args.create_pr
+        self.token: Optional[str] = args.token
+
+    def run(self) -> None:
+        logging.set_verbosity_info()
+        url = self.api.delete_files(
+            delete_patterns=self.patterns,
+            repo_id=self.repo_id,
+            repo_type=self.repo_type,
+            revision=self.revision,
+            commit_message=self.commit_message,
+            commit_description=self.commit_description,
+            create_pr=self.create_pr,
+        )
+        print(f"Files correctly deleted from repo. Commit: {url}.")
+        logging.set_verbosity_warning()
+
+
+class RepoFilesCommand(BaseHuggingfaceCLICommand):
+    @staticmethod
+    def register_subcommand(parser: _SubParsersAction):
+        repo_files_parser = parser.add_parser("repo-files", help="Manage files in a repo on the Hub")
+        repo_files_parser.add_argument(
+            "repo_id", type=str, help="The ID of the repo to manage (e.g. `username/repo-name`)."
+        )
+        repo_files_subparsers = repo_files_parser.add_subparsers(
+            help="Action to execute against the files.",
+            required=True,
+        )
+        delete_subparser = repo_files_subparsers.add_parser(
+            "delete",
+            help="Delete files from a repo on the Hub",
+        )
+        delete_subparser.set_defaults(func=lambda args: DeleteFilesSubCommand(args))
+        delete_subparser.add_argument(
+            "patterns",
+            nargs="+",
+            type=str,
+            help="Glob patterns to match files to delete.",
+        )
+        delete_subparser.add_argument(
+            "--repo-type",
+            choices=["model", "dataset", "space"],
+            default="model",
+            help="Type of the repo to upload to (e.g. `dataset`).",
+        )
+        delete_subparser.add_argument(
+            "--revision",
+            type=str,
+            help=(
+                "An optional Git revision to push to. It can be a branch name "
+                "or a PR reference. If revision does not"
+                " exist and `--create-pr` is not set, a branch will be automatically created."
+            ),
+        )
+        delete_subparser.add_argument(
+            "--commit-message", type=str, help="The summary / title / first line of the generated commit."
+        )
+        delete_subparser.add_argument(
+            "--commit-description", type=str, help="The description of the generated commit."
+        )
+        delete_subparser.add_argument(
+            "--create-pr", action="store_true", help="Whether to create a new Pull Request for these changes."
+        )
+        repo_files_parser.add_argument(
+            "--token",
+            type=str,
+            help="A User Access Token generated from https://huggingface.co/settings/tokens",
+        )
+
+        repo_files_parser.set_defaults(func=RepoFilesCommand)

parrot/lib/python3.10/site-packages/huggingface_hub/commands/tag.py

@@ -0,0 +1,159 @@
+# coding=utf-8
+# Copyright 2024-present, the HuggingFace Inc. team.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Contains commands to perform tag management with the CLI.
+
+Usage Examples:
+    - Create a tag:
+        $ huggingface-cli tag user/my-model 1.0 --message "First release"
+        $ huggingface-cli tag user/my-model 1.0 -m "First release" --revision develop
+        $ huggingface-cli tag user/my-dataset 1.0 -m "First release" --repo-type dataset
+        $ huggingface-cli tag user/my-space 1.0
+    - List all tags:
+        $ huggingface-cli tag -l user/my-model
+        $ huggingface-cli tag --list user/my-dataset --repo-type dataset
+    - Delete a tag:
+        $ huggingface-cli tag -d user/my-model 1.0
+        $ huggingface-cli tag --delete user/my-dataset 1.0 --repo-type dataset
+        $ huggingface-cli tag -d user/my-space 1.0 -y
+"""
+
+from argparse import Namespace, _SubParsersAction
+
+from requests.exceptions import HTTPError
+
+from huggingface_hub.commands import BaseHuggingfaceCLICommand
+from huggingface_hub.constants import (
+    REPO_TYPES,
+)
+from huggingface_hub.hf_api import HfApi
+
+from ..errors import HfHubHTTPError, RepositoryNotFoundError, RevisionNotFoundError
+from ._cli_utils import ANSI
+
+
+class TagCommands(BaseHuggingfaceCLICommand):
+    @staticmethod
+    def register_subcommand(parser: _SubParsersAction):
+        tag_parser = parser.add_parser("tag", help="(create, list, delete) tags for a repo in the hub")
+
+        tag_parser.add_argument("repo_id", type=str, help="The ID of the repo to tag (e.g. `username/repo-name`).")
+        tag_parser.add_argument("tag", nargs="?", type=str, help="The name of the tag for creation or deletion.")
+        tag_parser.add_argument("-m", "--message", type=str, help="The description of the tag to create.")
+        tag_parser.add_argument("--revision", type=str, help="The git revision to tag.")
+        tag_parser.add_argument(
+            "--token", type=str, help="A User Access Token generated from https://huggingface.co/settings/tokens."
+        )
+        tag_parser.add_argument(
+            "--repo-type",
+            choices=["model", "dataset", "space"],
+            default="model",
+            help="Set the type of repository (model, dataset, or space).",
+        )
+        tag_parser.add_argument("-y", "--yes", action="store_true", help="Answer Yes to prompts automatically.")
+
+        tag_parser.add_argument("-l", "--list", action="store_true", help="List tags for a repository.")
+        tag_parser.add_argument("-d", "--delete", action="store_true", help="Delete a tag for a repository.")
+
+        tag_parser.set_defaults(func=lambda args: handle_commands(args))
+
+
+def handle_commands(args: Namespace):
+    if args.list:
+        return TagListCommand(args)
+    elif args.delete:
+        return TagDeleteCommand(args)
+    else:
+        return TagCreateCommand(args)
+
+
+class TagCommand:
+    def __init__(self, args: Namespace):
+        self.args = args
+        self.api = HfApi(token=self.args.token)
+        self.repo_id = self.args.repo_id
+        self.repo_type = self.args.repo_type
+        if self.repo_type not in REPO_TYPES:
+            print("Invalid repo --repo-type")
+            exit(1)
+
+
+class TagCreateCommand(TagCommand):
+    def run(self):
+        print(f"You are about to create tag {ANSI.bold(self.args.tag)} on {self.repo_type} {ANSI.bold(self.repo_id)}")
+
+        try:
+            self.api.create_tag(
+                repo_id=self.repo_id,
+                tag=self.args.tag,
+                tag_message=self.args.message,
+                revision=self.args.revision,
+                repo_type=self.repo_type,
+            )
+        except RepositoryNotFoundError:
+            print(f"{self.repo_type.capitalize()} {ANSI.bold(self.repo_id)} not found.")
+            exit(1)
+        except RevisionNotFoundError:
+            print(f"Revision {ANSI.bold(self.args.revision)} not found.")
+            exit(1)
+        except HfHubHTTPError as e:
+            if e.response.status_code == 409:
+                print(f"Tag {ANSI.bold(self.args.tag)} already exists on {ANSI.bold(self.repo_id)}")
+                exit(1)
+            raise e
+
+        print(f"Tag {ANSI.bold(self.args.tag)} created on {ANSI.bold(self.repo_id)}")
+
+
+class TagListCommand(TagCommand):
+    def run(self):
+        try:
+            refs = self.api.list_repo_refs(
+                repo_id=self.repo_id,
+                repo_type=self.repo_type,
+            )
+        except RepositoryNotFoundError:
+            print(f"{self.repo_type.capitalize()} {ANSI.bold(self.repo_id)} not found.")
+            exit(1)
+        except HTTPError as e:
+            print(e)
+            print(ANSI.red(e.response.text))
+            exit(1)
+        if len(refs.tags) == 0:
+            print("No tags found")
+            exit(0)
+        print(f"Tags for {self.repo_type} {ANSI.bold(self.repo_id)}:")
+        for tag in refs.tags:
+            print(tag.name)
+
+
+class TagDeleteCommand(TagCommand):
+    def run(self):
+        print(f"You are about to delete tag {ANSI.bold(self.args.tag)} on {self.repo_type} {ANSI.bold(self.repo_id)}")
+
+        if not self.args.yes:
+            choice = input("Proceed? [Y/n] ").lower()
+            if choice not in ("", "y", "yes"):
+                print("Abort")
+                exit()
+        try:
+            self.api.delete_tag(repo_id=self.repo_id, tag=self.args.tag, repo_type=self.repo_type)
+        except RepositoryNotFoundError:
+            print(f"{self.repo_type.capitalize()} {ANSI.bold(self.repo_id)} not found.")
+            exit(1)
+        except RevisionNotFoundError:
+            print(f"Tag {ANSI.bold(self.args.tag)} not found on {ANSI.bold(self.repo_id)}")
+            exit(1)
+        print(f"Tag {ANSI.bold(self.args.tag)} deleted on {ANSI.bold(self.repo_id)}")

parrot/lib/python3.10/site-packages/huggingface_hub/inference/_generated/types/chat_completion.py

@@ -0,0 +1,301 @@
+# Inference code generated from the JSON schema spec in @huggingface/tasks.
+#
+# See:
+#   - script: https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-codegen.ts
+#   - specs:  https://github.com/huggingface/huggingface.js/tree/main/packages/tasks/src/tasks.
+from typing import Any, List, Literal, Optional, Union
+
+from .base import BaseInferenceType, dataclass_with_extra
+
+
+@dataclass_with_extra
+class ChatCompletionInputURL(BaseInferenceType):
+    url: str
+
+
+ChatCompletionInputMessageChunkType = Literal["text", "image_url"]
+
+
+@dataclass_with_extra
+class ChatCompletionInputMessageChunk(BaseInferenceType):
+    type: "ChatCompletionInputMessageChunkType"
+    image_url: Optional[ChatCompletionInputURL] = None
+    text: Optional[str] = None
+
+
+@dataclass_with_extra
+class ChatCompletionInputMessage(BaseInferenceType):
+    content: Union[List[ChatCompletionInputMessageChunk], str]
+    role: str
+    name: Optional[str] = None
+
+
+ChatCompletionInputGrammarTypeType = Literal["json", "regex"]
+
+
+@dataclass_with_extra
+class ChatCompletionInputGrammarType(BaseInferenceType):
+    type: "ChatCompletionInputGrammarTypeType"
+    value: Any
+    """A string that represents a [JSON Schema](https://json-schema.org/).
+    JSON Schema is a declarative language that allows to annotate JSON documents
+    with types and descriptions.
+    """
+
+
+@dataclass_with_extra
+class ChatCompletionInputStreamOptions(BaseInferenceType):
+    include_usage: bool
+    """If set, an additional chunk will be streamed before the data: [DONE] message. The usage
+    field on this chunk shows the token usage statistics for the entire request, and the
+    choices field will always be an empty array. All other chunks will also include a usage
+    field, but with a null value.
+    """
+
+
+@dataclass_with_extra
+class ChatCompletionInputFunctionName(BaseInferenceType):
+    name: str
+
+
+@dataclass_with_extra
+class ChatCompletionInputToolChoiceClass(BaseInferenceType):
+    function: ChatCompletionInputFunctionName
+
+
+ChatCompletionInputToolChoiceEnum = Literal["auto", "none", "required"]
+
+
+@dataclass_with_extra
+class ChatCompletionInputFunctionDefinition(BaseInferenceType):
+    arguments: Any
+    name: str
+    description: Optional[str] = None
+
+
+@dataclass_with_extra
+class ChatCompletionInputTool(BaseInferenceType):
+    function: ChatCompletionInputFunctionDefinition
+    type: str
+
+
+@dataclass_with_extra
+class ChatCompletionInput(BaseInferenceType):
+    """Chat Completion Input.
+    Auto-generated from TGI specs.
+    For more details, check out
+    https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-tgi-import.ts.
+    """
+
+    messages: List[ChatCompletionInputMessage]
+    """A list of messages comprising the conversation so far."""
+    frequency_penalty: Optional[float] = None
+    """Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing
+    frequency in the text so far,
+    decreasing the model's likelihood to repeat the same line verbatim.
+    """
+    logit_bias: Optional[List[float]] = None
+    """UNUSED
+    Modify the likelihood of specified tokens appearing in the completion. Accepts a JSON
+    object that maps tokens
+    (specified by their token ID in the tokenizer) to an associated bias value from -100 to
+    100. Mathematically,
+    the bias is added to the logits generated by the model prior to sampling. The exact
+    effect will vary per model,
+    but values between -1 and 1 should decrease or increase likelihood of selection; values
+    like -100 or 100 should
+    result in a ban or exclusive selection of the relevant token.
+    """
+    logprobs: Optional[bool] = None
+    """Whether to return log probabilities of the output tokens or not. If true, returns the log
+    probabilities of each
+    output token returned in the content of message.
+    """
+    max_tokens: Optional[int] = None
+    """The maximum number of tokens that can be generated in the chat completion."""
+    model: Optional[str] = None
+    """[UNUSED] ID of the model to use. See the model endpoint compatibility table for details
+    on which models work with the Chat API.
+    """
+    n: Optional[int] = None
+    """UNUSED
+    How many chat completion choices to generate for each input message. Note that you will
+    be charged based on the
+    number of generated tokens across all of the choices. Keep n as 1 to minimize costs.
+    """
+    presence_penalty: Optional[float] = None
+    """Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they
+    appear in the text so far,
+    increasing the model's likelihood to talk about new topics
+    """
+    response_format: Optional[ChatCompletionInputGrammarType] = None
+    seed: Optional[int] = None
+    stop: Optional[List[str]] = None
+    """Up to 4 sequences where the API will stop generating further tokens."""
+    stream: Optional[bool] = None
+    stream_options: Optional[ChatCompletionInputStreamOptions] = None
+    temperature: Optional[float] = None
+    """What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the
+    output more random, while
+    lower values like 0.2 will make it more focused and deterministic.
+    We generally recommend altering this or `top_p` but not both.
+    """
+    tool_choice: Optional[Union[ChatCompletionInputToolChoiceClass, "ChatCompletionInputToolChoiceEnum"]] = None
+    tool_prompt: Optional[str] = None
+    """A prompt to be appended before the tools"""
+    tools: Optional[List[ChatCompletionInputTool]] = None
+    """A list of tools the model may call. Currently, only functions are supported as a tool.
+    Use this to provide a list of
+    functions the model may generate JSON inputs for.
+    """
+    top_logprobs: Optional[int] = None
+    """An integer between 0 and 5 specifying the number of most likely tokens to return at each
+    token position, each with
+    an associated log probability. logprobs must be set to true if this parameter is used.
+    """
+    top_p: Optional[float] = None
+    """An alternative to sampling with temperature, called nucleus sampling, where the model
+    considers the results of the
+    tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10%
+    probability mass are considered.
+    """
+
+
+@dataclass_with_extra
+class ChatCompletionOutputTopLogprob(BaseInferenceType):
+    logprob: float
+    token: str
+
+
+@dataclass_with_extra
+class ChatCompletionOutputLogprob(BaseInferenceType):
+    logprob: float
+    token: str
+    top_logprobs: List[ChatCompletionOutputTopLogprob]
+
+
+@dataclass_with_extra
+class ChatCompletionOutputLogprobs(BaseInferenceType):
+    content: List[ChatCompletionOutputLogprob]
+
+
+@dataclass_with_extra
+class ChatCompletionOutputFunctionDefinition(BaseInferenceType):
+    arguments: Any
+    name: str
+    description: Optional[str] = None
+
+
+@dataclass_with_extra
+class ChatCompletionOutputToolCall(BaseInferenceType):
+    function: ChatCompletionOutputFunctionDefinition
+    id: str
+    type: str
+
+
+@dataclass_with_extra
+class ChatCompletionOutputMessage(BaseInferenceType):
+    role: str
+    content: Optional[str] = None
+    tool_calls: Optional[List[ChatCompletionOutputToolCall]] = None
+
+
+@dataclass_with_extra
+class ChatCompletionOutputComplete(BaseInferenceType):
+    finish_reason: str
+    index: int
+    message: ChatCompletionOutputMessage
+    logprobs: Optional[ChatCompletionOutputLogprobs] = None
+
+
+@dataclass_with_extra
+class ChatCompletionOutputUsage(BaseInferenceType):
+    completion_tokens: int
+    prompt_tokens: int
+    total_tokens: int
+
+
+@dataclass_with_extra
+class ChatCompletionOutput(BaseInferenceType):
+    """Chat Completion Output.
+    Auto-generated from TGI specs.
+    For more details, check out
+    https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-tgi-import.ts.
+    """
+
+    choices: List[ChatCompletionOutputComplete]
+    created: int
+    id: str
+    model: str
+    system_fingerprint: str
+    usage: ChatCompletionOutputUsage
+
+
+@dataclass_with_extra
+class ChatCompletionStreamOutputFunction(BaseInferenceType):
+    arguments: str
+    name: Optional[str] = None
+
+
+@dataclass_with_extra
+class ChatCompletionStreamOutputDeltaToolCall(BaseInferenceType):
+    function: ChatCompletionStreamOutputFunction
+    id: str
+    index: int
+    type: str
+
+
+@dataclass_with_extra
+class ChatCompletionStreamOutputDelta(BaseInferenceType):
+    role: str
+    content: Optional[str] = None
+    tool_calls: Optional[ChatCompletionStreamOutputDeltaToolCall] = None
+
+
+@dataclass_with_extra
+class ChatCompletionStreamOutputTopLogprob(BaseInferenceType):
+    logprob: float
+    token: str
+
+
+@dataclass_with_extra
+class ChatCompletionStreamOutputLogprob(BaseInferenceType):
+    logprob: float
+    token: str
+    top_logprobs: List[ChatCompletionStreamOutputTopLogprob]
+
+
+@dataclass_with_extra
+class ChatCompletionStreamOutputLogprobs(BaseInferenceType):
+    content: List[ChatCompletionStreamOutputLogprob]
+
+
+@dataclass_with_extra
+class ChatCompletionStreamOutputChoice(BaseInferenceType):
+    delta: ChatCompletionStreamOutputDelta
+    index: int
+    finish_reason: Optional[str] = None
+    logprobs: Optional[ChatCompletionStreamOutputLogprobs] = None
+
+
+@dataclass_with_extra
+class ChatCompletionStreamOutputUsage(BaseInferenceType):
+    completion_tokens: int
+    prompt_tokens: int
+    total_tokens: int
+
+
+@dataclass_with_extra
+class ChatCompletionStreamOutput(BaseInferenceType):
+    """Chat Completion Stream Output.
+    Auto-generated from TGI specs.
+    For more details, check out
+    https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-tgi-import.ts.
+    """
+
+    choices: List[ChatCompletionStreamOutputChoice]
+    created: int
+    id: str
+    model: str
+    system_fingerprint: str
+    usage: Optional[ChatCompletionStreamOutputUsage] = None

parrot/lib/python3.10/site-packages/huggingface_hub/inference/_generated/types/depth_estimation.py

@@ -0,0 +1,28 @@
+# Inference code generated from the JSON schema spec in @huggingface/tasks.
+#
+# See:
+#   - script: https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-codegen.ts
+#   - specs:  https://github.com/huggingface/huggingface.js/tree/main/packages/tasks/src/tasks.
+from typing import Any, Dict, Optional
+
+from .base import BaseInferenceType, dataclass_with_extra
+
+
+@dataclass_with_extra
+class DepthEstimationInput(BaseInferenceType):
+    """Inputs for Depth Estimation inference"""
+
+    inputs: Any
+    """The input image data"""
+    parameters: Optional[Dict[str, Any]] = None
+    """Additional inference parameters for Depth Estimation"""
+
+
+@dataclass_with_extra
+class DepthEstimationOutput(BaseInferenceType):
+    """Outputs of inference for the Depth Estimation task"""
+
+    depth: Any
+    """The predicted depth as an image"""
+    predicted_depth: Any
+    """The predicted depth as a tensor"""

parrot/lib/python3.10/site-packages/huggingface_hub/inference/_generated/types/image_to_text.py

@@ -0,0 +1,101 @@
+# Inference code generated from the JSON schema spec in @huggingface/tasks.
+#
+# See:
+#   - script: https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-codegen.ts
+#   - specs:  https://github.com/huggingface/huggingface.js/tree/main/packages/tasks/src/tasks.
+from typing import Any, Literal, Optional, Union
+
+from .base import BaseInferenceType, dataclass_with_extra
+
+
+ImageToTextEarlyStoppingEnum = Literal["never"]
+
+
+@dataclass_with_extra
+class ImageToTextGenerationParameters(BaseInferenceType):
+    """Parametrization of the text generation process"""
+
+    do_sample: Optional[bool] = None
+    """Whether to use sampling instead of greedy decoding when generating new tokens."""
+    early_stopping: Optional[Union[bool, "ImageToTextEarlyStoppingEnum"]] = None
+    """Controls the stopping condition for beam-based methods."""
+    epsilon_cutoff: Optional[float] = None
+    """If set to float strictly between 0 and 1, only tokens with a conditional probability
+    greater than epsilon_cutoff will be sampled. In the paper, suggested values range from
+    3e-4 to 9e-4, depending on the size of the model. See [Truncation Sampling as Language
+    Model Desmoothing](https://hf.co/papers/2210.15191) for more details.
+    """
+    eta_cutoff: Optional[float] = None
+    """Eta sampling is a hybrid of locally typical sampling and epsilon sampling. If set to
+    float strictly between 0 and 1, a token is only considered if it is greater than either
+    eta_cutoff or sqrt(eta_cutoff) * exp(-entropy(softmax(next_token_logits))). The latter
+    term is intuitively the expected next token probability, scaled by sqrt(eta_cutoff). In
+    the paper, suggested values range from 3e-4 to 2e-3, depending on the size of the model.
+    See [Truncation Sampling as Language Model Desmoothing](https://hf.co/papers/2210.15191)
+    for more details.
+    """
+    max_length: Optional[int] = None
+    """The maximum length (in tokens) of the generated text, including the input."""
+    max_new_tokens: Optional[int] = None
+    """The maximum number of tokens to generate. Takes precedence over max_length."""
+    min_length: Optional[int] = None
+    """The minimum length (in tokens) of the generated text, including the input."""
+    min_new_tokens: Optional[int] = None
+    """The minimum number of tokens to generate. Takes precedence over min_length."""
+    num_beam_groups: Optional[int] = None
+    """Number of groups to divide num_beams into in order to ensure diversity among different
+    groups of beams. See [this paper](https://hf.co/papers/1610.02424) for more details.
+    """
+    num_beams: Optional[int] = None
+    """Number of beams to use for beam search."""
+    penalty_alpha: Optional[float] = None
+    """The value balances the model confidence and the degeneration penalty in contrastive
+    search decoding.
+    """
+    temperature: Optional[float] = None
+    """The value used to modulate the next token probabilities."""
+    top_k: Optional[int] = None
+    """The number of highest probability vocabulary tokens to keep for top-k-filtering."""
+    top_p: Optional[float] = None
+    """If set to float < 1, only the smallest set of most probable tokens with probabilities
+    that add up to top_p or higher are kept for generation.
+    """
+    typical_p: Optional[float] = None
+    """Local typicality measures how similar the conditional probability of predicting a target
+    token next is to the expected conditional probability of predicting a random token next,
+    given the partial text already generated. If set to float < 1, the smallest set of the
+    most locally typical tokens with probabilities that add up to typical_p or higher are
+    kept for generation. See [this paper](https://hf.co/papers/2202.00666) for more details.
+    """
+    use_cache: Optional[bool] = None
+    """Whether the model should use the past last key/values attentions to speed up decoding"""
+
+
+@dataclass_with_extra
+class ImageToTextParameters(BaseInferenceType):
+    """Additional inference parameters for Image To Text"""
+
+    max_new_tokens: Optional[int] = None
+    """The amount of maximum tokens to generate."""
+    # Will be deprecated in the future when the renaming to `generation_parameters` is implemented in transformers
+    generate_kwargs: Optional[ImageToTextGenerationParameters] = None
+    """Parametrization of the text generation process"""
+
+
+@dataclass_with_extra
+class ImageToTextInput(BaseInferenceType):
+    """Inputs for Image To Text inference"""
+
+    inputs: Any
+    """The input image data"""
+    parameters: Optional[ImageToTextParameters] = None
+    """Additional inference parameters for Image To Text"""
+
+
+@dataclass_with_extra
+class ImageToTextOutput(BaseInferenceType):
+    """Outputs of inference for the Image To Text task"""
+
+    generated_text: Any
+    image_to_text_output_generated_text: Optional[str] = None
+    """The generated text."""

parrot/lib/python3.10/site-packages/huggingface_hub/inference/_generated/types/sentence_similarity.py

@@ -0,0 +1,27 @@
+# Inference code generated from the JSON schema spec in @huggingface/tasks.
+#
+# See:
+#   - script: https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-codegen.ts
+#   - specs:  https://github.com/huggingface/huggingface.js/tree/main/packages/tasks/src/tasks.
+from typing import Any, Dict, List, Optional
+
+from .base import BaseInferenceType, dataclass_with_extra
+
+
+@dataclass_with_extra
+class SentenceSimilarityInputData(BaseInferenceType):
+    sentences: List[str]
+    """A list of strings which will be compared against the source_sentence."""
+    source_sentence: str
+    """The string that you wish to compare the other strings with. This can be a phrase,
+    sentence, or longer passage, depending on the model being used.
+    """
+
+
+@dataclass_with_extra
+class SentenceSimilarityInput(BaseInferenceType):
+    """Inputs for Sentence similarity inference"""
+
+    inputs: SentenceSimilarityInputData
+    parameters: Optional[Dict[str, Any]] = None
+    """Additional inference parameters for Sentence Similarity"""

parrot/lib/python3.10/site-packages/huggingface_hub/inference/_generated/types/token_classification.py

@@ -0,0 +1,51 @@
+# Inference code generated from the JSON schema spec in @huggingface/tasks.
+#
+# See:
+#   - script: https://github.com/huggingface/huggingface.js/blob/main/packages/tasks/scripts/inference-codegen.ts
+#   - specs:  https://github.com/huggingface/huggingface.js/tree/main/packages/tasks/src/tasks.
+from typing import List, Literal, Optional
+
+from .base import BaseInferenceType, dataclass_with_extra
+
+
+TokenClassificationAggregationStrategy = Literal["none", "simple", "first", "average", "max"]
+
+
+@dataclass_with_extra
+class TokenClassificationParameters(BaseInferenceType):
+    """Additional inference parameters for Token Classification"""
+
+    aggregation_strategy: Optional["TokenClassificationAggregationStrategy"] = None
+    """The strategy used to fuse tokens based on model predictions"""
+    ignore_labels: Optional[List[str]] = None
+    """A list of labels to ignore"""
+    stride: Optional[int] = None
+    """The number of overlapping tokens between chunks when splitting the input text."""
+
+
+@dataclass_with_extra
+class TokenClassificationInput(BaseInferenceType):
+    """Inputs for Token Classification inference"""
+
+    inputs: str
+    """The input text data"""
+    parameters: Optional[TokenClassificationParameters] = None
+    """Additional inference parameters for Token Classification"""
+
+
+@dataclass_with_extra
+class TokenClassificationOutputElement(BaseInferenceType):
+    """Outputs of inference for the Token Classification task"""
+
+    end: int
+    """The character position in the input where this group ends."""
+    score: float
+    """The associated score / probability"""
+    start: int
+    """The character position in the input where this group begins."""
+    word: str
+    """The corresponding text"""
+    entity: Optional[str] = None
+    """The predicted label for a single token"""
+    entity_group: Optional[str] = None
+    """The predicted label for a group of one or more tokens"""